Accurately estimating the bearing of a target with two hydrophones requires knowing the precise distance between them.However,in practice,it is difficult to measure this distance accurately due to the influence of cur...Accurately estimating the bearing of a target with two hydrophones requires knowing the precise distance between them.However,in practice,it is difficult to measure this distance accurately due to the influence of current.To solve this problem,we propose a method for extracting the time-domain Green's function between two points in multi-ship scenarios and for extracting the time-domain waveform arrival structure between two hydrophones in real-time based on long samples of ship radiation noise cross-correlation.Using the cross-correlation function of the radiated noise from any ship located in the end-fire direction of the two hydrophones,we can estimate the distance between the hydrophones in real-time.To verify the accuracy of our estimation,we compare the result of azimuth estimation with the actual azimuth based on the azimuth estimation of a cooperative sound source in the maritime environment.Our experimental results show that the proposed method correctly estimates the distance between two hydrophones that cannot be directly measured and estimates the position of a cooperative sound source 4 km away with an average deviation of less than 1.2°.展开更多
Due to the induced polarization(IP)eff ect,the sign reversal often occurs in timedomain airborne electromagnetic(AEM)data.The inversions that do not consider IP eff ect cannot recover the true umderground electrical s...Due to the induced polarization(IP)eff ect,the sign reversal often occurs in timedomain airborne electromagnetic(AEM)data.The inversions that do not consider IP eff ect cannot recover the true umderground electrical structures.In view of the fact that there are many parameters of airborne induced polarization data in time domain,and the sensitivity diff erence between parameters is large,which brings challenges to the stability and accuracy of the inversion.In this paper,we propose an inversion mehtod for time-domain AEM data with IP effect based on the Pearson correlation constraints.This method uses the Pearson correlation coeffi cient in statistics to characterize the correlation between the resistivity and the chargeability and constructs the Pearson correlation constraints for inverting the objective function to reduce the non uniqueness of inversion.To verify the eff ectiveness of this method,we perform both Occam’s inversion and Pearson correlation constrained inversion on the synthetic data.The experiments show that the Pearson correlation constrained inverison is more accurate and stable than the Occam’s inversion.Finally,we carried out the inversion to a survey dataset with and without IP eff ect.The results show that the data misfit and the continuity of the inverted section are greatly improved when the IP eff ect is considered.展开更多
基金Project supported by the National Natural Science Foundation of China (Grant No.62171148)。
文摘Accurately estimating the bearing of a target with two hydrophones requires knowing the precise distance between them.However,in practice,it is difficult to measure this distance accurately due to the influence of current.To solve this problem,we propose a method for extracting the time-domain Green's function between two points in multi-ship scenarios and for extracting the time-domain waveform arrival structure between two hydrophones in real-time based on long samples of ship radiation noise cross-correlation.Using the cross-correlation function of the radiated noise from any ship located in the end-fire direction of the two hydrophones,we can estimate the distance between the hydrophones in real-time.To verify the accuracy of our estimation,we compare the result of azimuth estimation with the actual azimuth based on the azimuth estimation of a cooperative sound source in the maritime environment.Our experimental results show that the proposed method correctly estimates the distance between two hydrophones that cannot be directly measured and estimates the position of a cooperative sound source 4 km away with an average deviation of less than 1.2°.
基金This paper was fi nancially supported by the National Natural Science Foundation of China(Nos.42030806,41774125,41904104,41804098)the Pioneer Project of Chinese Academy of Sciences(No.XDA14020102).
文摘Due to the induced polarization(IP)eff ect,the sign reversal often occurs in timedomain airborne electromagnetic(AEM)data.The inversions that do not consider IP eff ect cannot recover the true umderground electrical structures.In view of the fact that there are many parameters of airborne induced polarization data in time domain,and the sensitivity diff erence between parameters is large,which brings challenges to the stability and accuracy of the inversion.In this paper,we propose an inversion mehtod for time-domain AEM data with IP effect based on the Pearson correlation constraints.This method uses the Pearson correlation coeffi cient in statistics to characterize the correlation between the resistivity and the chargeability and constructs the Pearson correlation constraints for inverting the objective function to reduce the non uniqueness of inversion.To verify the eff ectiveness of this method,we perform both Occam’s inversion and Pearson correlation constrained inversion on the synthetic data.The experiments show that the Pearson correlation constrained inverison is more accurate and stable than the Occam’s inversion.Finally,we carried out the inversion to a survey dataset with and without IP eff ect.The results show that the data misfit and the continuity of the inverted section are greatly improved when the IP eff ect is considered.
